Clinical and computational exploration of IRS1 and Pancreastatin genetic variants in metabolic response to metformin-sulfonylurea therapy

Background Individuals with type 2 diabetes mellitus (T2DM) show variable responses to metformin-sulfonylurea therapy. Genetic variation in insulin signaling and metabolic regulation, particularly in insulin receptor substrate-1 (IRS1) and pancreastatin (PST), may contribute to this variability. This study assessed the influence of IRS1 (rs1801278) and PST (rs9658664) polymorphisms on baseline metabolic profiles and response to combination therapy.Methods We enrolled 202 diabetic individuals receiving metformin-sulfonylurea therapy. Clinical and biochemical parameters were measured at baseline and follow-up. Genotyping for IRS1 (rs1801278) and PST (rs9658664) was performed using PCR-RFLP and statistically analyzed by SPSS (v.27). Exploratory molecular docking analyses were performed to examine mutation-dependent differences in PST interactions with insulin-signaling proteins.Results Renal complications were more prevalent among non-responders (p = 0.029). IRS1 and PST genotypes were not associated with therapeutic response. Individuals with IRS1 TT genotype exhibited higher baseline cholesterol, triglyceride, and LDL levels (p = 0.05). Docking analyses suggested mutation-dependent differences in PST interactions with insulin receptor, IRS1, and GRP78. Metformin showed slightly stronger predicted binding to insulin receptor and IRS1 than sulfonylurea.Conclusion Although IRS1 and PST polymorphisms did not show association with treatment response, genotype-based metabolic variability and in silico analyses suggest functional effects on insulin-signaling pathways, highlighting the potential of personalized medicine approaches for optimizing antidiabetic therapy.

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Journal
Personalized Medicine
Published
2026-10-28
DOI
https://doi.org/10.1080/17410541.2026.2753761
Primary Topic
Pharmacogenetics and Drug Metabolism
Type
article
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article

Clinical and computational exploration of IRS1 and Pancreastatin genetic variants in metabolic response to metformin-sulfonylurea therapy

Tabrez Faruqui, Asma Imran Ansari, Sushma Verma, Aliya Abbas Rizvi et al.
2 links
Personalized Medicine
Pharmacogenetics and Drug Metabolism
article

Clinical and computational exploration of IRS1 and Pancreastatin genetic variants in metabolic response to metformin-sulfonylurea therapy

Tabrez Faruqui, Asma Imran Ansari, Sushma Verma, Aliya Abbas Rizvi, Farzana Mahdi, Mohammad Abbas, Zeba Siddiqi
article en

Abstract

Background Individuals with type 2 diabetes mellitus (T2DM) show variable responses to metformin-sulfonylurea therapy. Genetic variation in insulin signaling and metabolic regulation, particularly in insulin receptor substrate-1 (IRS1) and pancreastatin (PST), may contribute to this variability. This study assessed the influence of IRS1 (rs1801278) and PST (rs9658664) polymorphisms on baseline metabolic profiles and response to combination therapy.Methods We enrolled 202 diabetic individuals receiving metformin-sulfonylurea therapy. Clinical and biochemical parameters were measured at baseline and follow-up. Genotyping for IRS1 (rs1801278) and PST (rs9658664) was performed using PCR-RFLP and statistically analyzed by SPSS (v.27). Exploratory molecular docking analyses were performed to examine mutation-dependent differences in PST interactions with insulin-signaling proteins.Results Renal complications were more prevalent among non-responders (p = 0.029). IRS1 and PST genotypes were not associated with therapeutic response. Individuals with IRS1 TT genotype exhibited higher baseline cholesterol, triglyceride, and LDL levels (p = 0.05). Docking analyses suggested mutation-dependent differences in PST interactions with insulin receptor, IRS1, and GRP78. Metformin showed slightly stronger predicted binding to insulin receptor and IRS1 than sulfonylurea.Conclusion Although IRS1 and PST polymorphisms did not show association with treatment response, genotype-based metabolic variability and in silico analyses suggest functional effects on insulin-signaling pathways, highlighting the potential of personalized medicine approaches for optimizing antidiabetic therapy.

Personalized Medicine
Era's Lucknow Medical College and Hospital (IN)
Good health and well-being
Openalex Percentile: Top 10%
Pharmacogenetics and Drug Metabolism
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